Producer Services Agglomeration and Carbon Emission Reduction—An Empirical Test Based on Panel Data from China

Abstract

Although China has a high rate of economic development, it still faces the problems of unstable industrial structure, low industrial level, and large carbon emissions, which pose huge challenges to China’s sustainable development. China is working hard to develop producer services to achieve industrial transformation and reduce carbon emissions. In this context, there is an extremely urgent need to conduct academic research on changes in producer service agglomeration and carbon emissions. Whether the producer service industry has agglomeration characteristics, and whether the producer service industry affects carbon emissions through multiple paths, are issues worthy of attention. Therefore, this paper takes China as the research area, selects the provincial administrative unit as the research sample, and conducts research on these issues by using exploratory spatial data analysis methods and various spatial econometric models under the guidance of the relevant theories of new economic geography. Our research finds that producer services have significant spatial agglomeration characteristics, and they also have significant spatial differentiation patterns. In addition, the agglomeration of producer services can significantly promote the reduction of carbon emissions and can show obvious spillover effects. Finally, in response to the research conclusions of this paper, we also put forward countermeasures and suggestions from the perspective of the common development of producer service industry and manufacturing industry, hoping to promote China’s transformation from industrial economy to service economy, to maximize the use of producer service industry accumulated dividends.

Impact of Producer Service Agglomeration on Carbon Emission Efficiency and Its Mechanism: A Case Study of Urban Agglomeration in the Yangtze River Delta

“…This study also eliminates the sample outliers via 1% winsorization. Model (8) shows that the quadratic term of APS and its spatial lag is still significantly positive.…”

“…It is generally believed that producer services are rooted in the intermediate demand of the manufacturing industry and are an industrial form gradually developed around the manufacturing industry [7]. With the continuous improvement of transportation conditions and information technology, the intrinsic requirements such as geographical proximity and "face-to-face" contact between production services and the manufacturing industry have been weakened, and the scope of transactions has expanded, showing a significant trend of spatial agglomeration [8].…”

Spatial Dependence of SO2 Emissions and Energy Consumption Structure in Northern China

“…To investigate whether the energy consumption structure has a spatial effect on SO2 emissions, the spatial autocorrelation of SO2 must first be analyzed. To test whether there is spatial autocorrelation among regional variables, generally according to the spatial autocorrelation Moran I index [43][44][45], the calculation formula is as follows (1):…”

Spatial correlation between producer services agglomeration and carbon emissions in the Yangtze River Economic Belt based on point-of-interest

“…In terms of methodology, scholars have evaluated industrial agglomeration by calculating the location quotient index and Gini coefficient 22 , 23 . The agglomeration of producer services is evaluated by calculating the producer services agglomeration index 24 . Meanwhile, making use of the spatial Durbin model, dynamic GMM model, and STIRPAT model to reflect how industrial agglomeration and producer services agglomeration impact environmental pollution in Chinese cities 25 – 27 .…”

“…Therefore, it is an important channel to develop a low-carbon economy and achieve green development. Existing researches generally find that producer services agglomeration can significantly reduce carbon emissions and have a spatial spillover effect 24 . It positively impacts carbon efficiency through the scale effect and technology spillover effect.…”